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Analytics Information Architect

Summary

Work location will be:
425 BETTER WAY
Make your mark with us!
To learn more about working at U.S. Venture, watch this video: Life at U.S....

Description

Work location will be:

425 BETTER WAY

Make your mark with us!

To learn more about working at U.S. Venture, watch this video: Life at U.S. Venture

POSITION SUMMARY

The Analytics Information Architect would be the custodian of enterprise data model, with a focus on master data management (MDM) and predictive analytics in a big data environment, to enable insight and analytics capabilities, represented by cloud computing, open-source programming, and analytics-based decision making.

The role requires close partnership and collaboration with the organization's Data Resource Management Team, Data Scientists, Data Analysts, and Business Intelligence Analysts to create a mature data management and advanced analytics ecosystem.

JOB RESPONSIBILITIES

* Forward looking: Be the strategist and designer for data strategy, infrastructure, and workflow processes: connecting with ERP and Data warehouses, focus on BI and predictive / prescriptive analytics uses so that we proactively create a road map and eco-system for future growth and monetization of data/info (internally and potentially externally). Implications of open source programming, cloud computing, IoT, Blockchain, and other technological changes/trends.

* Translate user requirements and business use cases to conceptual, logical, and physical data models and workflow processes.

* Act as bridge and translator between business data SMEs (subject matter experts) and technical data SMEs and guide requirements conversations through a structured approach that builds business confidence in the process.

* Translate a business glossary into logical and physical data models, and assist / support engineers in their development / testing / implementation effort.

* Create a tiered enterprise data management architecture to support analytics, using a combination of relational, dimensional and flat data models, depending on business context, type of data, and use cases.

* Identify appropriate sources for the data science team's data needs, create the necessary data mapping and transformation rules (with a focus on business objective and processes) and assist the data engineering team in staging / curating the data for advanced analytics

* Facilitate the data scientists, data analysts, and business intelligence analysts in using master data and analytic data by walking them through the framework, roadmap, model structure, and workflow using business scenarios familiar to them.